The rapid pace of innovation and the constantly exploding collection of possibilities is a major contributor to the fun we all have in digital jobs. There is never a boring moment, there is never time when you can’t do something faster or smarter.

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. They never had to worry that they have to be in a persistent forward motion… sometimes just to stay current.

This reality powers my impostor syndrome, and (yet?) it is the reason that I love working in every dimension of digital. We are at an inflection point in humanity’s evolution where in small and big ways, we can actually change the world.

With that context, this post is all about career management in the digital space. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. I would offer that the higher-order-bits in each of the three sections will provide valuable food-for-thought for anyone in a digital role.

The post has three clusters of advice. The first two are from editions of my newsletter, The Marketing – Analytics Intersect (it goes out weekly, and is now my primary publishing channel, sign up!). The third section was sparked by a question a friend who works at a digital agency asked: Will I lose my job to automation soon? (The answer was, yes.)

The Now section provides advice on how investing in growing your Analytical Thinking will contribute to greater success in the role you are in. The Next section provides advice on what you should be doing to invest in yourself to get ready for the depth and breadth change Artificial Intelligence is going to bestow upon us (regardless of your business role). The Long section shares a thought experiment I want you to undertake to figure out your career three years from now.

One more change reflective of the times we live in… Your employer used to be responsible for your career, this is for the most part no longer true. Your employer would send you to trainings to help push your career forward, this is for the most part no longer true. Your employer/manager would help you figure out the skills you can develop, this is for the most part no longer true. It is now all on you. Hence… Take control.

Ready?

The Now Career Plan: Analytics Experience vs. Analytical Thinking

Check the requirements listed in any digital analytics job and you'll notice a long laundry list looking for analytics experience.

Years of having used tool x. Years and years of practice with R or "Big Data." Years of proficiency in analyzing m campaigns for n channels resulting in production of z reports.

When you go to the interview, the hiring company will proceed to ask questions that test your competency in the listed job requirements.

This is normal.

Reflecting on my experience, it is not sufficient.

Test for analytics experience AND explore the level of analytical thinking the job candidate possesses.

Analytical thinking is 6,451 times more crucial in the long-term success of the candidate and the value they'll add to your company.

Analytical Thinking: Skills, Interviewing, Value.

Analytical thinking is a collection of skills.

It is creative problem solving. It is working systematically and logically when dealing with complex tasks. It is exploring alternatives from multiple angles to find a solution. It is a brilliant evaluation of pros and cons, and achieving the balance that is right for that specific moment. It is always knowing that the answer to what's two plus two is always in what context? It is being able to recognize patterns. It is knowing that every worthy life decision is a multivariate regression equation (hence the quest to identify all the variables in that equation and their weights). It is the possession of critical thinking abilities. And, most of all it is being able to seek and see the higher order bits.

Beautiful, right?

If I have the immense privilege of interviewing you, expect us to spend a lot of time on the elements mentioned above.

One sample strategy: Expect that I'll ask open-ended questions (If a company has 90% Reach on TV, why the heck do they need digital?). Then, regardless of what you say I'll politely but forcefully push back, to explore the depth and breadth of analytical thinking you bring to the table.

If you hire strong analytical thinkers, of any background, you are hiring people who will be adaptable, who'll grow and flex with your organization and needs. They'll have the mental agility to think smart and move fast. They'll ask child-like simple questions that'll lay bare your complex strategic challenges. Hire them. And, if they don't know tool x… You can teach them which buttons to press.

Caring and Feeding Your Analytical Thinking.

If you are an analytical thinker, there are many ways in which you can keep feeding and stretching the synapses in your brain. There is always more you can learn.

In a business context, request an hour to talk to people three levels above you in the organization. Ask them what they worry about, ask them what they are solving for, ask them how they measure success, ask them what are two things on the horizon that they are excited about. So on and so forth. You'll see things very differently, and you'll think very differently when you go back to work.

I'd mentioned being able to look at every situation from multiple angles. (Think of the famous bullet time scene in the Matrix.) Hence, a personal strategy of mine is to look well outside my area of expertise to help me improve my analytical thinking capabilities.

The Supreme Court deals with situations that are insanely complex – even when they appear to be stunningly simple on the surface. There are so many lessons to be learned.

My favorites are the ones I massively disagree with. Citizens United is one such example. I could not possibly disagree with it more. Yet reading through the deep details helped me see the multiple facets being explored, the reasoning used by the other side. I learned a lot.

I go in open-minded, and at times have my mind changed. A good example of this Justice Scalia's opinion in Gonzales v. Raich and the use of the Commerce Clause. And, he was not a man with whom I have overlapping views on anything. I appreciate him stretching my mind in this case.

Optimal Starting SCOTUS Starting Points.

If you would like to pursue my personal strategy, here are a collection of cases to use as starting points.

Some cases are very dear to me, I truly love them, there is a lot to learn from them as you explore the back and forth of the debate, the majority opinion and the dissenting one (or ones).

Loving v. Virginia is close to my heart, it is the reason I can legally marry my wife. It was just 50 years go!

Obergefell v. Hodges brought immense to our family as we celebrated the right of all Americans to marry. Justice Kennedy's opinion is a thing of beauty. And, it is also useful to read Justices Scalia and Thomas' strong and powerful dissents.

Texas v. Johnson said that prohibition on desecration of the American flag was a violation of the right to free speech. Of the many wonderful things about America, the First Amendment is at the top and distinctly unique. The court looked beyond the jingoistic distractions the flag always attracts, and protected what's critical.

As I'd mentioned above, there is much to learn from cases that are heartbreaking

Dred Scott v. Sandford held that African Americans, free or slaves, could not be considered American citizens and undid the Missouri Compromise. It contained the infamous quote "[black men] had no rights which the white man was bound to respect."

Buck v. Bell is perhaps the one that is a deep, deep source of pain for me, it a decision that still stands. The court upheld forced sterilizations for those with "intellectual disabilities" and contained the despicable phrase "three generations of imbeciles are enough."

Korematsu v. United States, legalized the shameful internment of American citizens with any Japanese ancestry. It is still on the books, and places extraordinary power in the President of the US to do what they want to people who might not look like "Americans." People like me.

Each case, regardless of if I agree with the opinion or disagree, helps push my thinking. It makes me a better analyst, a better employee, a better start-up founder.

I've added a differentiated collection of links above to take you to sources, I hope they'll help feed your analytical thinking.

For the Busy Human On The Go, An Alternative.

Given everything above, I absolutely LOVE the More Perfect podcast.

Jad Abumrad and his team are magnificent storytellers. For each episode, they take one case and explore it from multiple directions. They are entertaining, engaging and deeply informative.

Season two kicked of with… Korematsu! I thought I knew all angles of this case. Yet, towards the end you'll hear two loud silences in a conversation with Judge Richard Posner. Make sure you hear what he says. I have profound respect for Judge Posner, he is brilliant. And, in those two moments, he both made me deeply uncomfortable and appreciate complexity.

The problem is simple. In Wisconsin Republicans in power massively gerrymandered voting districts (something the Democrats also do when in power). Unlike the past where little sophistication was applied, this time sophisticated algorithms and computers were brought into play. Resulting in more effective gerrymandering.

End result: Democrats won 53% of the votes but only 39% of the seats.

You might think: OMG! CRAZY BEANS! What happened to one person one vote!

Well, the case was heard by the Supreme Court last week. And, everything's quite complicated (analytical thinking!). Listen to the episode for that.

What's even more material for us is that Justice Kennedy wants to know how can he figure out that a district has been "too" gerrymandered. There is no real standard, nothing the Justices can use.

Math to the rescue!

Nicholas Stephanopoulos and Eric McGhee created an Efficiency Gap formula to assess how bad the gerrymandering was. (More here, PDF.)

I won't spoil it for you, let Professor Moon Duchin explain it to in the podcast. It is a thing of beauty.

You'll learn how to create smarter formulas in your job, how to solve complicated and ambiguous challenges with simple assumptions, and how to not to grow too close to your formulas – rather evolve them over time to be smarter.

In 23 mins, it will make you a better Analyst.

If you follow the overall guidance in this section, you’ll continue to invest and grow the one skill you’ll need in every digital career: Sophisticated analytical thinking.

The Next Career Plan: Prepping For An AI-First World

Even with all the hype related to all things Artificial Intelligence, I feel people are not taking the topic seriously enough. That the big, broad implications for the very near future are not causing us to sit up, take notice, and change our strategies (personal and professional).

Or, maybe I'm just too deep into this stuff. :)

I had two big ah-ha moments that have changed my view if humans can be competitive in any field compared to what technology will spring forth. I call the two elementsl Collective Continuous Learning and Complete Day One Knowledge, they are harbingers of exciting possibilities for what we can do with AI (and it to us).

The topic of AI is vast, and I’m not even including all the layers and flavors. The more I learn, the more I realize how little I know. My heartfelt recommendation is that every professional should be curious about AI and try to stay abreast with as many new dimensions as they can. After the first few months, you’ll find your own sweetspot that’ll catch your fancy.

Here are the collection of books, videos, people and learning opportunities from my sweetspot…

Books.

I want to recommend three books. None focusses on digital marketing or analytics. Each tackles humans and the possibilities for humans. Hence they’ve had a profound impact on my thinking about humanity’s future (and via that route, my career plans).

The span of Mr. Harari's thinking is truly grand, and he's a great storyteller. I am less pessimistic than Mr. Harari about the 300 year outcome (as you'll read in my post above on AI), but he's influenced my thinking deeply.

AI will birth numerous incredible solutions for humanity, but the most magical bits will come from Artificial General Intelligence. Some people think of it as Superintelligence. Mr. Bostrom does a fantastic job of exploring the possibilities. Let me know if you get scared or excited by the end. :)

I love the way Mr. Tegmark writes, and there is something magical about his ability to distill all living things, you, me, watermelons, to up quarks, down quarks and nand gates! I was so inspired by his writing that I wrote to him my personal prediction for humanity looking 300 years out.

Videos.

Current development of Intelligence is in silos, I'm glad when someone pulls all the experts from around the world in an attempt to guide humanity's efforts.

The Future of Life Institute hosted a conference in Asilomar in Jan 2017 with just such a purpose. The entire list of videos is well worth watching, prioritize the individual ones: Beneficial AI 2017

In any space that is having the kind of exponential growth like AI, your best bet is to find people who trust and listen to what they are saying/doing.

We are blessed with a ton of experts, practitioners and futurists. I encourage you to curate your own list.

Here are the ones I follow as closely as I can: Sebastian Thrun, Jürgen Schmidhuber, Demis Hassabis, and Andrew Ng.

I watch videos of all their talks on YouTube or tune in to livestreams of their presentations. I read articles they write. I have alerts for them. Luckily they are so darn busy, they pace their public speaking/writing. :)

You can follow their work using strategies you currently use for others you stay in touch with.

Learning.

If you are slightly technically oriented and would like to start your journey of acquiring technical knowledge in the space, Udacity is a great place to go.

If you are deeply technically oriented, you already know where to go and don’t need my pointers!

I’m sure you’ll notice I’ve not given you specific advice for your next career move. One reason: We are in a moment where each of us has to know all the changes coming, all the possibilities arising, and then figure out that answer for ourselves.

The above books, videos, people and lessons will help you discover the right answer for yourself.

The Long Career Plan: Automation & Your Value To A Company

People are scared of automation.

It is logical. The AI revolution will bring a ton of automation that will eliminate current white-collar jobs in large numbers.

Yet, by the end of this thought experiment, you might see that looking out over the nest 25-30 years, we can deal with automation (/elimination of our current jobs).

Here's the thought: If tomorrow everything you currently do, inside that box, is completely automated… What's your value?

Pause.

Think about it carefully in terms of personal implications.

For the bravest among you, think of what's the value of your Agency/Company.

If you are anything like me, you are super-scared. Some of you are likely super-excited as well.

Don't be scared. Take action.

It is not as crazy as you think to envision that you could be completely automated out. In small pieces this has already happened.

Media example: Campaigns to create, target and deliver results for driving app downloads is now almost entirely automated.

Analytics example: There are already buttons in your tools that automate finding of anomalies in your data that your leaders most need to pay attention to. Eliminating the need for the known knowns and automatically providing the known unknowns and unknown unknowns.

An example that combines the both for even more effective automation: With smart creative, smart bidding, and smart targeting there is no need for any human to touch AdWords or soon a whole lot of your Display campaigns. The results of Data Driven Attribution modeling, which use data from *all* digital campaigns, can now be directly plugged into AdWords which means without any reporting/analysis the platform will automatically optimize for the highest profit for your business – with no human involvement. This is not the future, it is Nov 2017.

Back to the whiteboard.

On top of the box with the stuff you do, write the word Automated.

Ponder now what's your value.

You'll see there are two areas where you can add value. The area before the box, the area after the box.

If you are a Marketer…

You can shift to taking more ownership of the inputs that go into your current job (which remember is now automated). Shift to a responsibility that requires a deeper understanding of your Prospects and Customers at a human level. Now, because of that beautiful knowledge, take ownership of the entire process of identifying the optimal creative assets required for any great Marketing campaign. Then, step up and move to the other side of the box… Own the use and deployment of large scale machine learning services to understand every human, which results in creating the simplest most meaningful experience across all digital touch-points. And then… I'm taking you so far away from your current box… expand the outcomes you own from just the transactional to building deeper years-long beyond-pimpy relationships with your customers.

And suddenly…

You hate the freaking box you are in as a Marketer today. You want to expand your responsibility to own these deeply meaningful things that Machine Learning and our Deep Neural Networks won't touch for a while. You want to feel the true joy that comes from doing meaningful things like figuring out how to build relationships or unleash the full and beautiful power of amazing creative (in ads, in apps, on sites, in products), and so many more exciting things that you were born to do.

Now, you are not scared about automated. You can't wait for your current job to be automated away.

:)

I have the above scenario and the wonderful possibilities for Analysts as well. It is also very exciting, as you’ll discover when you do the whiteboarding exercise for yourself.

Now. I totally get that your entire job is not getting automated tomorrow. But, I suspect you'll be surprised though how fast that is coming. For Nurses. For Truck drivers. For Baristas. For… Everyone. Collect a handful of the smartest people you know, draw a box on a whiteboard, have a discussion.

This thought experiment is just one way to think through the implications of what’s ahead of us. In my blog post on the artificial intelligence opportunity, you’ll see another way I framed how to think this through…

The above framing is a bit more in the higher-order-bit spirit.

I recommend the thought experiment. When you’re done: Step one, have a plan. Step two, execute. Step three, joy. Step four, follow the advice in section one (Now) and section two (Next) of this blog post and start investing in the personal growth you’ll need to move to these new more joy-inducing meaningful jobs.

Your career is in your hands, and I deeply believe it is going to be bright. Seize the moment!

As always, it is your turn now.

Considering the Now moment, is there something unique you do to invest in growing your analytical thinking capabilities? How are you preparing for the Next moment, who are you reading, who are you listening to? Considering the next 25 years in our space, how far do you think automation will go? How are you approaching your personal evolution with the Long moment horizon in mind? How about your company’s?

Comments

My first realization is that the world is in front of me, yet I'm not seeing anything. You look at that same world and see patterns that are telling you something completely different. I appreciate having my eyes opened.

I am curious what you see before and after the box for Analysts. I promise to do the exercise with my team, but if there is anything I've learned from this post it is that you are going to come up with something completely different.

Tom: Because I know Analysts so well, being one myself, it is likely a longer post.

Briefly though… Analysts focus too narrowly on one part of the food chain. On the right side of the box for example are a whole host of things related to creating a sense of urgency for action. One simple strategy for that is leveraging smart predict analytics around what data is saying you should do. That's just the data side, there are a whole host human/emotional strategies to create a sense of urgency.

Most analysts don't do this at all. For now, ML will likely need humans to do this. Gainful and joyous employment for you and me!

But I am curious to understand what and how these soft skills (if that is indeed the case that they are of value?) can be turned into opportunities to pivot your career and the types of roles/jobs they will create?

Can you picture what these jobs would be and how would you define an ethics centric or empathy centric job?

For analysts I think you will have to lean more towards "creativity" and "separate good data from bad data". For every step ML and AI takes, there will be 10 new models applicable to the problem domain you are in. Being able to understand which of the available to apply with the available data and how to present it to the machine will require great domain knowledge for a long time to come.

The even better analysts will be able to look at the best model and understand how to tweak it to be even better for the given problem. I believe that the further we get with ML the more we will be able to rely on creativity rather than excellent skills in mathematics for improving the existing models

Trotte: You are completely right about the reliance on us for creativity of various kinds.

Over the long term it will be interesting to see what facets of creativity stay with humans. In the lobby of the PartnerPlex in B40 at Google in Mountain View, there is a piano that, automatically, plays music written by an AI. I am always stunned at how good the music is. Not yet Beethoven, but better than so many others that are good at this stuff!

Simon: A whole bunch of soft skills will be valuable in the interim (during the phase ML continues to become ever more effective at doing more in more jobs), some might even be relevant even on the long run.

Here's what I want you to consider, say three decades out…

Today in Marketing there are fifteen or so departments, for larger companies it might also involve two or three agencies. Across all these layers, you need decisions made and action to be taken on those. Lots and lots of soft skills required (often sadly even more than data).

In a couple of decades lots of the above points will be connected via automation and intelligence. You simply won't have humans involved between information assessment – identification of influencing actions – begging the right leaders/departments – taking action. No humans, no softskills.

Some roles will still remain where humans will still need to be involved, requiring soft skills.

I think mostly importantly we need to evolve ourselves daily. Knowing the things happening around us is essential.

I was in a box doing repetitive tasks but recently I started learning new topics through MOOCs like edx coursera udemy etc. They have excellent topics for AI, deep learning, UI UX strategy, analytics strategy & more. Also I started exploring new startups & their ideas.

The world seemed much bigger than the tasks I was doing. Because of learning new topics & putting out an hour or two daily for learning new things, I could evolve myself to the tasks where AI or ML might not help.

I guess in coming years human human interaction will be the most important skills to have.

But still I am not skeptical about AI & ready to evolve according to it.

It brings such joy to find a fellow lover of the Supreme Court. I am a voracious consumer of all things scotus. Now I can show your blog post to my boss and do all my reading during work hours. :)

I have not been consciously leaning into developing my analytical thinking nor the broader implications on AI. I would argue that your recommendations in Next are a way of pushing our analytical thinking forward.

My biggest reminder is that I am in control. Our organization like many does quarterly goals and reviews. This narrows the horizon that I as an individual bring to career discussion. It is the behavior that lulls us from the medium and long term planning encouraged in this post.

Thanks for the list of books and people in the middle of the post. Books ordered, alerts created.

Great and timely article as I begin a job search. I've come to realize that for the past 3 years, I largely have been doing the same tasks with the same tools…not growing much. I just had a conversation with an old friend of mine last night where we both admitted our fear of becoming obsolete and talked about strategies to stay marketable. Your post is far more futuristic than where our discussion went.

As for your discussion on machine learning and AI, a man that I have a great deal of respect for is James Cameron. He is uber creative and very technical. He is working on a new Terminator movie that will be a direct sequel to Terminator 2 pretending that Terminators 3 – 5 never existed. In recent interviews he makes it clear that AI and machine learning are going to be a big part of the story.

"Technology has always scared me, and it's always seduced me. People ask me: "Will the machines ever win against humanity?" I say: "Look around in any airport or restaurant and see how many people are on their phones. The machines have already won." It's just [that] they've won in a different way. We are co-evolving with our technology. We're merging. The technology is becoming a mirror to us as we start to build humanoid robots and as we start to seriously build AGI — general intelligence — that's our equal. Some of the top scientists in artificial intelligence say that's 10 to 30 years from now. We need to get the damn movies done before that actually happens!"

A C S:: I agree with you on Mr. Cameron. He has always been a few steps ahead of us in having a vision for technology can do. I had not read the quote you share, but I'm amazed at how the time horizon he shares is one I believe is going to be transformative for humanity in this context.

I have to admit one place where I had a humble difference in pov with Mr. Cameron is the humanoid robot bit. Yes, there might be a bit of that, but in the near-term we will take control of the biological interfaces with technology to become far superior versions of humans. In the long-term, I'm not sure these inefficient things called bodies will be the form we manifest (and now we are looking 100 – 200 years out).

My role in web analytics has changed immensely since I started 7 years ago. Back then reporting was manual, tedious and took up the bulk of my time with less emphasis on analysis – the 'analysis' was the role I was hired for. Fast forward to 2017 and reporting makes up less than 10% of my role and is fully automated into beautiful interactive dashboards.

Now the majority of my time is spent on providing actionable insights not just on my company's website but for the app and other digital platforms. My role is now more of a digital analyst which keeps me on my toes, ever evolving which I love about working in this industry.

Am I scared of automation? No. I've been embracing it and as long as you up-skill then I see no reason than to appreciate the new opportunities it brings.

Rich, heavy, ever insightful as always. Thank you for sharing your thoughts. It will take some time to digest in the days ahead.

Now, I was at a Data Science conference yesterday and one of the speakers said something like "we're living in the age of the rise of humans" alluding to the fact that automation will, contrary to the general anxiety, actually help humans develop better skills, and do better jobs.

As a step one I believe that humans will connect and be infused with all kinds of intelligence, memory and compute power. We will be unimaginably better versions of humans. Your Data Science speaker was right.

Technology (AGI, Super Intelligence, Quantum Computing…) will continue its ceaseless progress and become more intelligent and competent than all humans combined. What happens then, say 50 years from now, will be phase two.

Thanks for replying. OK, this certainly takes off in a scary direction. 'Upgraded humans infused with tech and compute power' was clearly not on my speaker's agenda. All he meant was that AI would provide us better information and metrics to work with so we can do better, more meaningful jobs while the lesser mundane, redundant labour such as data entry would be handled conveniently by the machines.

[Probably off-topic: I also personally struggle with imagining 'phase two' with my christian belief. Are we in denial or is this vision of ordinary human>cyborg>AI-domination a result of too much sci-fi?]

Wumi: "Phase Two" is a deeply personal reflection for all of us spiritual people (of traditional faiths or otherwise). It brings up tough questions, answers to some that we are usually unwilling to accept/think through.

To your sci-fi point… To the extent my humble skills allow, I believe movies spark our imagination, but their imagination is far too limited by the anchors of the current reality. Over a long period of time, I'm optimistic about our future as a species (and I'll share my thinking on this in TMAI #100, if you are on my newsletter please check it out and share your reflection with me).

Thank you for another forward-thinking post! I look forward to exploring the resources you've recommended to stay abreast of the movements in AI. Occam's Razor is certainly the top of my list for this!

For me this movement seems so much more exciting than it is scary. It means automating and minimizing the soul-destroyingly dull parts of my job and focusing more on the reasons that I got into digital marketing and analytics in the first place. The things I was passionate about during my marketing courses in university; thinking critically and analytically to understand our consumers and strategy on a deep level and then applying creative solutions to take action and help the business thrive. These skills require a human (at least for the foreseeable future). I think the new focus of effort will only help humans become more valuable in their roles.

This reminds me of your post on the ideal balance between DC | DR | DA. Not many marketers or analysts get excited about the highly repeatable DC | DR work (at least none that I know), but some do find security there. I'll admit, this was the case for me. I was unsure about automating/ minimizing DC | DR in my role. But when we did I was able to focus on great insights and my value to the organization increased 100x along with my job satisfaction. I hope that advancements in AI will bring the same kinds of transformation!

Most agencies are fearful of the automation that is quickly coming to every part of Digital Marketing. Agencies that have a deeper history in television or print where here was no need to learn anything new for decades are truly freaking out.

I share the optimism for similar reasons to the ones Justin mentiones in his comment.

We will all have access to the same core Machine Learning algos that power automation which makes it vital to do the box thought experiment you recommend. What is our true value as an Agency? How can we extend what is at the very core of our competence into new areas? There are plenty of problems to solve.

I appreciate your very useful resources to explore the future of work, when it comes to analytics and AI!

A typical question for practical application of AI is how to deal with situations when our (limited) human mind cannot grasp very complex decisions made by the machines. In your link to the "Superintelligence" video, Bart Selman provides a very interesting rebuttal to this concern. In fact, as AI keeps advancing, machines will soon be able to generate explanations to their decisions that are … human understandable!

I think that the role of Analysts will evolve to identify new opportunities to utilize AI to help companies not only address the issues the companies traditionally try to resolve (in the field of ecommerce: drive more traffic, increase conversion rate, etc.), but also identify solutions for the problems that currently fly under our radar (answering questions we have yet to ask.)

Alex: To add to your example, Google has also shared publicly that it has approaches to get an "explanation" from Deep Neural Networks how they are, for the lack of a better word, thinking.

For a little while, while we are still in the world of narrow AI, this will work. The problem is when the complexity they manage, the scale at which they work, the size of challenges they are solving.

Here's a metaphor, let me know if it helps (/if you agree)… Consider Squirrels and humans. A human can explain, in simple, logical, detailed terms, exactly how we approach growing carrots or designing a rocket ship. Yet, at no level can a Squirrel understand anything we explain.

We are, at some point in the next five years, going to be the Squirrels. :)

Avinash.
PS: I'm not saying this is a good thing or a bad thing. I am not freaking out about it. It is what it is.

Thanks Avinash, your metaphor is spot on! While I don't personally think it's a great thing to be a non-contributing squirrel, I agree that I have no choice of accepting or rejecting this situation, it simply exists without my input. I do wonder if it would take AI developers only 5 years to get to the point when as humans we would be able to understand the machines.

In the meantime, perhaps we should use your "So, what" test? Surely as squirrels we don't understand the process of growing carrots or designing a rocket ship, however, we CAN understand the implications of having carrots and rocket ships at our disposal and even possibly observe the patterns behind different harvest seasons and geographical availability of such goods.

I've been thinking whether 'good' data (i.e. Complete, accurate and facts-reflecting) can still be bad from an ethic-centric POV because good data capture both good and bad decisions made by human, so it contains all kinds of biases in it. The challenge is how to turn 'good' data into 'great' data (i.e. Bias-free data) if it's indeed possible….what do you think?

I foresee a backlash against automated marketing and a return to human, we're already seeing it in journalism. Software and teams of robots engaging with folks is (at least right now) fairly obvious on social media and generally aggravates our customers.

Recent statistics show subscriptions are up at old school content creators like The Atlantic and the Wall Street Journal – people want to physically know who is creating their content and engage with them.

Leah: I'm sure you are right. There will be some people who don't want to change, they want to remain in their current jobs with their current skills. This was true for the last handful of transformative revolutions.

I'm afraid, I don't think this is equivalent to current lameness with Chatbots (which you are right to criticize) or subscriptions to news publications. Change is coming, regardless of if a small group wants it or not. It will touch every facet of humanity. We might resist it, progress will still not be stopped (because on multiple dimensions it will be the superior state most of us want).

A brilliant job of pointing out the difference between Analysts vs Analytical Thinking.

I have gone to a number of interviews in my career where only experience was counted and rarely did people stress test my analytical thinking. Still I have continued to invest in growing my analytical thinking by taking formal courses that share tools that I can use to be a stronger thinker. I've also used strategies like getting exposed to multiple facets of the business, and multiple businesses to bring a broader view to my job.

We were talking about our next career step (I've been working as marketer for different industries) because we are 40's years old and we feel that anything from our experience will be useful next years. I'm specially excited with AI but I don't have experience in Digital areas. I'm looking for courses abroad (I'm living in Brazil) to help me to approach to AI.

Do you think that is it realistic? Can you recommend some courses or universities? Thanks in advance.

Great article as usual. Lots to think about and apply. I appreciate it. In the last few years, I have made the transition from the digital marketing to digital analytics side. Last few roles, I did this because I felt it was the hottest part of digital and since I started optimizing web sites for search in 1997 and was beta customers for all the majors, Google, Bing, Yahoo, Linkedin, FB, Twitter, etc.
I think you are right. I have come up in the time before the internet and then now, after for over 20 post internet.

Its just not that simple, neat or uniform. Adoption of any technology is **NOT** seamless. It does not move the way we think. There are many other factors that govern the adoption of any major technical wave. I am not disagreeing with you, I am on your side. I just think there are alot of things on the other side. My experience is, data is very messy. The data that exists at company is disparate, siloed and can be very faulty most of the time. Just because something is automated, does not make it right and or correct. Garbage in the machine means garbage out.

I love Google Analytics and I teach it, look me up, we are connected on Linkedin. Yet, Google Analytics data can be wrong. I have used premium and have had to email support when the data being pushed through the API and the user interface is incorrect. Everyone thinks technology..any technology is seamless, easy, quick and perfectly efficient, its not. This goes for all technology. You need redundant systems as in this case, server side analytics, to validate each application.

Next, what you don't mention is the following: if the application is paid for, off the books and working fine, there has to be a really big value proposition to change it. Example, EDI. Developed in the 70s, still used by major corporations today. Do not negate the impact of finance, accounting, stockholder value and the nature of CEO compensation today.

I say all this to say, I believe there plenty of work and opportunities for people who can get in the weeds, learn new applications quickly and determine those opportunities before or outside of the box. In the last three years, I have used Tableau and now we use PowerBI. I am taking courses in data science brushing up on stats, decision matrix and other the areas. I give you the credit for that because I have learned I have to keep learning. Just give some thought to what I am saying….I am out here, working in corporations that want me to get their digital data right and connected to their enterprise data…..its just not as clean, easy or neat nor it will be. Just my opinion. Thanks for all your thoughts, hard work and willingness to share with us. Sincerely, Mary Kay Lofurno

Mary: If I'm understanding you right, you have done all the recommended things in this post… Hence you find yourself in an excellent position from a career perspective! Congratulations.

I could not agree more with you about GIGO, it is an issue on multiple dimensions (not just Analytics) and something that we have to address as an industry.

On your second point, I believe the sense of urgency will be higher this time around compared to your example of EDI. The scale of the change, the fact that a lot of it will sit in the cloud, and that it's benefit will not be incremental but revolutionary will make it hard to ignore. If they ignore, it will be easier to die faster.

I try to keep current. I am not perfect. I am married, have a family and have multiple other demands on my time. I just love to learn. It can be addiction for me if I am not careful.

The GIGO issue is HUGE. Yes, multiple dimensions and in my opinion is a real problem when it comes to the AI wave you are talking about. Most companies are barely at the point of taking a good analytics/analysis run at their ERP data, let alone their digital data. Disparate sources of data in multiple places. On the digital side, its improper set up of tag managers, how the web site is set up and the technology they use [example angular]. Not using the right products when the business calls for it. Like I said, data is very very messy and there is alot that is just plain wrong.

EDI, well ok, might go a little quicker now with the cloud making solid gains….but again, do not discount the impact of finance, accounting, current perceived gestalt of how to optimize shareholder value and CEO compensation.

I've read all three of your posts on AI in one sitting, it has been perhaps the most mind-blowing hour of my life when it comes to professional education.

My mind is too full of possibilities to make a thoughtful comment. I simply want to thank you Avinash for the incredible generosity with which you share your knowledge. It is rare for someone who is so far ahead of the rest of us in the field to work so hard to give back. Thank you.

Hope you don't mind giving a quick career advice to a young digital marketer who just found your blog and is spending his off-week studying it :)

Current position is with an agency trade desk, managing an in-house programmatic team for one large account. Between keeping up with live campaigns, reporting, answering client questions, chasing down publishers and training my two lovely analysts, my day is always busy. My position is equivalent of 'Director, Programmatic Operations" at other agencies, essentially operations manager + (technical) account manager hybrid role. However, my goal is to work towards a senior technical position, working on advising/implementing digital marketing strategies (something like mapping out digital-to-retail attribution for a CPG company, or aggregating ecomm data to create actionable audience profile for a fashion company, off the top of my head).

I am strongly considering going back to school for statistics or computer science. Went to a business school and worked in corporate tax before, so critical thinking and attention to detail helped me with successful career transition. To go even further, or to work with innovative minds such as yours, I feel the need for better understanding of math and creative problem solving.

Would you recommend going back to school for it, or focusing on transitioning into other roles?

John: The best strategy is to speak to professionals who hold positions one level senior to the one you are targeting in the near term, and asking them how they got there. I think you'll be surprised at how many paths lead to the destination you desire. This will also expose you to local limitations or opportunities (in your geo, in your specific industry, in your specific discipline).

One other thought to consider, looking out a decade… Restricting the view to our industry… I am noticing an increasing amount of automation on the technology side. Less code deployment, less hyper-customization required, less need for technical translations to make the marketing and analytics magic happen. Consider Search, it is now possible to a good degree to automate bidding, targeting, creative to be powered by automated audience strategies, behaviour across digital channels (including attribution across visits and channels), site and app analytics data. This mostly works today, it will for sure work completely in a couple years, in a decade what technical roles are there? Not the ones you and I are seeing today.

Rather than playing with the systems were we apply technical skills today, there will be roles in building the systems themselves, making them smarter, writing intelligence that teases out biases or help overcome incompleteness in the learning data-sets, applying algorithmic approaches to help these smart entities to explain themselves, and so on and so forth. Loads and loads of really exciting technical roles. Possibly consider evaluating if you should aim for where the puck is going to be. :)

I'm unaware of your current wonderful skills, but earning for the above would be a combination of university (super-advanced math) and online (python, udacity courses above).

I went to the Marketing Festival in Prague and saw your presentation about AI and a look at what the future holds. Last year I graduated (24 years) with my bachelor degree and went working for an Agency as CRO specialist.

Reading your article and seeing your presentation has made me think a lot about the future, especially my future. The examples you give to the farmer and the field full of perfect lettuce looks like a small example of AI but can have a major impact on humanity.

We have seen the start of a new age, the block-chain technology is also one of them. The mass on earth has no idea what block-chain technology is and can do. And even If you talk about AI
they are thinking that you came out the movie Star Trek.

I have the idea that there will become a big split between people who can adapt all the new technologies and understand the impact that the new technologies can have and people who just want it the old way. The potential of AI and the block-chain technology for humanity is immense. New companies with the use of AI can help humanity with problems we couldn't solve in years.

Thanks for your vision! It becomes an exciting future for the further development of humanity!

Your insights are spot on when it comes to the need for mental agility and continuing training. Things are moving so fast now in the tech age that it's up to everyone to have the ability to adapt to changes in their sectors.

Aliki: Today most common implementations of Machine Learning are predictions. "What is in this picture?" "What is the next move in GO?"

In context of digital analytics… In Google Analytics you can see a metric called Session Quality. It predicts how close a person is to a conversion. That is a good example of the intersection of the two things you mention.

You can imagine other ideas in that spirit. Any place we have too much data, too much variation in data, and to many "branches" for humans to make any sense of them. Ripe for ML. :)